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相关概念视频

Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
Cytotoxic T Cells-mediated Immune Response01:27

Cytotoxic T Cells-mediated Immune Response

Cytotoxic T cells are a vital component of the immune system. They have the remarkable ability to identify and target antigens on infected or abnormal cells. These antigens often originate from intracellular pathogens such as viruses or abnormal proteins cancer cells produce.
Immunological surveillance is the ability of immune cells to monitor and eliminate infected cells with intracellular pathogens, neoplastically transformed cells, and cells with non-self antigens. Cytotoxic T cells and NK...
Tumor Immunotherapy01:27

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.
Cancer Vaccines01:30

Cancer Vaccines

Cancer treatment vaccines are a rapidly evolving field that offers a promising approach to immunotherapy. Unlike traditional vaccines that prevent diseases, cancer treatment vaccines are designed to treat existing cancers by stimulating the immune system to recognize and attack cancer cells.
Cancer vaccines come in two categories: preventive (prophylactic) and treatment (active). Preventive vaccines, such as the Human Papillomavirus (HPV) vaccine, protect against viruses that cause certain...

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相关实验视频

Updated: May 24, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

开发一个深度学习模型,以利用先天的基因组预测癌症免疫治疗反应.

Kai Yan, Zhiheng Zhou, Sihao Liu

    IEEE journal of biomedical and health informatics
    |March 28, 2025
    PubMed
    概括
    此摘要是机器生成的。

    预测癌症患者对免疫检查点抑制剂 (ICI) 的反应至关重要. 一种新的深度学习模型基于生殖线全基因组测序数据准确识别可能受益于ICI的患者.

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    科学领域:

    • 在瘤学瘤学.
    • 基因组学就是基因组学.
    • 生物信息学是一种生物信息学.

    背景情况:

    • 免疫检查点抑制剂 (ICI) 已经彻底改变了癌症治疗,但响应率仍然很低 (15-30%).
    • 由于高成本和潜在的不良影响,预测患者对ICI的反应至关重要.
    • 需要准确的预测方法来优化ICI治疗选择.

    研究的目的:

    • 开发和验证一种新的计算模型,用于预测癌症患者对ICI的反应.
    • 为了确定与ICI治疗疗效和患者存活率相关的生殖系基因组变异.
    • 通过预测生物标志物增强个性化癌症治疗策略.

    主要方法:

    • 编译了来自37名黑色素瘤患者和700名公开可用的ICI治疗癌症患者的生殖线全基因组测序 (WES) 数据.
    • 开发了一种新的双通道注意力神经网络 (DANN) 模型,用于预测ICI响应.
    • 对DANN识别的基因和与患者生存相关的基因组变异进行了丰富分析.

    主要成果:

    • DANN模型实现了高预测准确度 (平均0.95) 和AUC (0.98),超过了传统的机器学习方法.
    • 丰富分析表明,影响宿主免疫系统的生殖系变异广泛影响ICI反应.
    • 确定了一组12个基因,其中基因组变异与ICI治疗后患者存活率显著相关.

    结论:

    • DANN模型提供了一个有前途的工具,可以准确预测癌症患者的ICI反应.
    • 生殖系基因组变异在调节宿主免疫力和随后对ICI的反应方面发挥着重要作用.
    • 鉴定的12个基因组可以作为潜在的生物标志物,用于预测ICI治疗癌症患者的生存结果.